About This Architecture

Dual-pass categorization engine combining fast heuristic regex matching with fallback LLM zero-shot inference for automated support ticket classification. Raw ticket logs flow through text sanitization and deduplication, then branch into a high-speed heuristic pass evaluating SAP T-Codes and keyword patterns with sub-millisecond latency. Unmatched tickets escalate to an LLM smart lane that constructs dynamic structured dossiers and validates against category manifesto before final assignment. This hybrid approach balances speed, accuracy, and cost by reserving expensive LLM inference only for tickets failing fast-path heuristics. Fork and customize this workflow on Diagrams.so to adapt categorization rules, add new keyword patterns, or integrate your own LLM endpoints.

People also ask

How can I build a cost-effective ticket categorization system that uses fast heuristics first and only invokes expensive LLM inference when needed?

This dual-pass categorization engine uses a heuristic keyword fast lane with regex scanning for high-confidence matches (sub-1ms latency), then routes unmatched tickets to an LLM smart lane for zero-shot inference. Text sanitization and deduplication prepare raw ticket logs, while an exact-match parser gate validates LLM results against category manifesto before final assignment.

Dual-Pass Categorization Engine Workflow

AWSadvancedmachine-learningNLPticket-classificationhybrid-architecturecost-optimization
Domain: Ml PipelineAudience: ML engineers and data scientists building intelligent ticket classification systems on AWS
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Created by

July 23, 2026

Updated

August 18, 2026 at 12:05 AM

Type

network

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